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Manual transcription of audio databases for automatic speech recognition (ASR) training is a costly and time-consuming process. State-of-the-art hybrid ASR systems that are based on deep neural networks (DNN) can exploit un-transcribed foreign data during ...
Attending to an object can strongly modulate the neural processing of this object. Using average EEG, it was shown that small differences in the focus of attention yield large and long lasting changes in brain dynamics (Plomp et al, 2009). Here, we show th ...
A two-level procedure designed for the estimation of constitutive model parameters is presented in this paper. The neural network (NN) approach at the first level is applied to achieve the first approximation of parameters. This technique is used to avoid ...
A dynamic mixture of iron complexes was used as a colorimetric sensor for sulfated glycosaminoglycans. The sensing ensemble was prepared by mixing [FeCl2(H2O)4] with dipicolylamine, the functionalized bipyridyl ligand N-(6-aminohexyl)-4'-methyl-2,2'-bipyri ...
In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network to ...
Human gait analysis and classification is the process of identifying individuals by their walking manners. Computerized gait analysis using neural networks and fuzzy logic has become an integral part of the treatment decision-making process. Authors propos ...
The early detection of changes in the level and composition of algae is essential for tracking water quality and environmental changes. Current approaches require the collection of a specimen which is later analyzed in a laboratory: this slow and expensive ...
This study proposes a new technique for real-time building energy modelling and event detection using kernel regression. We show that this technique can exceed the performance of conventional neural network algorithms, and do so by a large margin when the ...
With ever-increasing power densities, Dynamic Thermal Management (DTM) techniques have become mainstream in today’s systems. An important component of such techniques is the thermal trigger. It has been shown that predictive thermal triggers can outperform ...